Integration of data mining techniques to postgreSQL database manager system
Integración de técnicas de minería de datos al sistema de administrador de base de datos postgreSQL
Date
2019
2019
Author
Amelec, Viloria
Camargo Acuña, Genesis Yulie
Alcázar Franco, Daniel Jesús
Hernández-Palma, Hugo
Fuentes Pacheco, Jorge
Pallares Rambal, Etelberto
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Abstract
Data mining is a technique that allows to obtain patterns or models from the gathered data. This technique is applied in all kind of environments such as in the biological field, educational and financial applications, industry, police, and political processes. Within data mining there are several techniques, among which are the induction of rules and decision trees which, according to various studies carried out, are among the most used. This research analyzes decision tree data mining techniques and induction rules to integrate several of its algorithms into PostgreSQL database management system (DBMS). Through an experiment, it was found that when the algorithms are integrated to the manager, the response times and the results obtained are higher.
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